Tissue strain imaging using a wavelet transform-based peak search algorithm

2007 ◽  
Vol 54 (6) ◽  
pp. 1118-1130 ◽  
Author(s):  
Hani Eskandari ◽  
Septimiu E. Salcudean ◽  
Robert Rohling
Keyword(s):  
Wavelet Transform ◽  
Search Algorithm ◽  
Strain Imaging ◽  
Tissue Strain ◽  
Peak Search

Determine the Architecture of ANNs by Using the Peak Search Algorithm and Delta Values

2021 ◽  
Author(s):  
Mihirini Wagarachchi ◽  
Asoka Karunananda ◽  
Dinithi Navodya
Keyword(s):  
Search Algorithm ◽  
Peak Search

scholarly journals Dual-Mass MEMS Gyroscope Parallel Denoising and Temperature Compensation Processing Based on WLMP and CS-SVR

Micromachines ◽  
2020 ◽  
Vol 11 (6) ◽  
pp. 586 ◽  
Author(s):  
Longkang Chang ◽  
Huiliang Cao ◽  
Chong Shen
Keyword(s):  
Wavelet Transform ◽  
Support Vector Regression ◽  
Temperature Compensation ◽  
Linear Prediction ◽  
Search Algorithm ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Temperature Error ◽  
Support Vector ◽  
Mixed Features

For the sake of decreasing the effects of noise and temperature error on the measurement accuracy of micro-electro-mechanical system (MEMS) gyroscopes, a denoising and temperature drift compensation parallel model method based on wavelet transform and forward linear prediction (WFLP) and support vector regression based on the cuckoo search algorithm (CS-SVR) is proposed in this paper. First, variational mode decomposition (VMD) is proposed in this paper, which is aimed at dividing the output signal of the gyroscope into intrinsic mode functions (IMFs); then, the IMFs are classified into three features—drift, mixed, and pure noise features—by the sample entropy (SE) value. Second, a wavelet transform and forward linear prediction (WFLP) are combined to remove the noise from the mixed features. Meanwhile, the drift feature is compensated by support vector regression based on the cuckoo search algorithm (CS-SVR). Finally, through reconstruction, the final signal is obtained. Experimental results demonstrate that the VMD-SE-WFLP-CS-SVR method proposed in this paper can decrease noise and compensate the temperature error effectively (angular random walking value is optimized from 1.667°/√h to 0.0667°/√h and the bias stability is reduced from 30°/h to 4°/h). In terms of denoising, the performance of the WFLP algorithm is superior to the wavelet threshold and FLP, as it combines their advantages; furthermore, in terms of temperature compensation, the proposed CS-SVR algorithm uses the cuckoo search algorithm to find the optimal parameters of SVR, improving the accuracy of the model.

Investigation of Radiofrequency Ultrasound-Based Fibrotic Tissue Strain Imaging Method Employing Endogenous Motion

2019 ◽  
Vol 38 (9) ◽  
pp. 2315-2327 ◽  
Author(s):  
Andrius Sakalauskas ◽  
Rytis Jurkonis ◽  
Sigita Gelman ◽  
Arūnas Lukoševičius ◽  
Limas Kupčinskas
Keyword(s):  
Strain Imaging ◽  
Imaging Method ◽  
Fibrotic Tissue ◽  
Tissue Strain
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